Uma Nova Meta-heurística Adaptativa Baseada em Vetor de Avaliações para Otimização de Portfólios de Investimentos

  • Omar Andres Carmona Cortes IFMA
  • Leticia de Fátima Corrêa Costa Universidade Estadual do Maranhão
  • Jo˜ao Pedro Augusto Costa
Keywords: Meta-Heuristicas, Multiobjetivo, ABC, PSO, DE, Otimização de Portfólios

Abstract

This article describes a new adaptive metaheuristic based on a vector evaluated approach for solving multiobjective problems. We called our proposed algorithm Vector Evaluated Meta-Heuristic. Its main idea is to evolve two populations independently, exchanging information between them, i.e., the first population evolves according to the best individual of the second population and vice-versa. The choice of which algorithm will be executed on each generation is carried out stochastically among three evolutionary algorithms well known in the literature: PSO, DE, ABC. In order to evaluate the results, we used an established metric in multiobjective evolutionary algorithms called hypervolume. Tests have shown that the adaptive metaheuristic reaches the best hyper-volumes in three of ZDT benchmarks functions and, also, in two portfolios of a real-world problem called portfolio investment optimization. The results show that our algorithm improved the Pareto curve when compared to the hypervolumes of each heuristic separately.

Downloads

Download data is not yet available.
Published
2019-12-09
How to Cite
Carmona Cortes, O., Corrêa Costa, L., & Augusto Costa, J. (2019). Uma Nova Meta-heurística Adaptativa Baseada em Vetor de Avaliações para Otimização de Portfólios de Investimentos. Inteligencia Artificial, 22(64), 85-101. https://doi.org/10.4114/intartif.vol22iss64pp85-101